source("regression_functions.R")
fig.path <- "results/"



### define outcomes and control variables
yvars<- paste0("exogamy_l",c(1:11,15:16)) ## 
yvars_std <- paste0(yvars,"_std")
controls.geo <- c("ruggedness_nunn_puga" ,  "elevation"  ,  "malaria_suit_max",
                  "TSI_CRU_mean_1901_1920" , "temperature_fao" , "precipitation_fao",  "coast_log"  ,
                  "LONGNUM", "agric_suit", "LATNUM")
controls.hist <- c("explorers_log", "cities_log", "capital_log","dist.prot_log" , "dist.print_log","popc_mean_1720_1890_log")
controls.ind <- c("age","age.sq","age.m","age.m.sq")
base.x <-  c(controls.ind, controls.geo,controls.hist)

### define analysis countries
sample_countries_hance <- unique(dhs$iso3c[dhs$sample_country_hance==1])



m.list.cntr2 <- lapply(yvars_std, function(dv){
  felm(as.formula(RegFor( y = dv , x = c("hance_crops5_sum_15km_std","pubspc.23_poly_std", base.x,"terr_frac_cell_alt") ,
                          FE = "country_survey_round" , 
                          IV="0", clust = "loc.id_pubs_poly")),
       data=dhs,subset=LONGNUM!=0 & iso3c%in%sample_countries_hance)
})



m.list.cntr1 <- lapply(yvars_std, function(dv){
  felm(as.formula(RegFor( y = dv , x = c("hance_crops5_sum_15km_std","pubspc.23_poly_std", base.x) ,
                          FE = "country_survey_round" ,
                          IV="0", clust = "loc.id_pubs_poly")),
       data=dhs,subset=LONGNUM!=0 & iso3c%in%sample_countries_hance)
})


#### prepare regression results for visual output
ticks <- seq(19.5,1,-1.5)
out.ls <- lapply(m.list.cntr2, function(x){
  get_plot_data(x,coef_no=c(1,2))
})
out.df <- do.call(rbind,out.ls)
out.df$dv <- c(rep(paste0("Exogamy L",c(1:10)),each=2),rep(paste0("Exogamy L","11-14"),each=2),rep(paste0("Exogamy L",c(15:16)),each=2))
out.df$what <- factor(rep(c("Cash Crops (Diversity Control)","Publications (Diversity Control)"),13))
ord. <- c(ticks+0.4,ticks-0.2)
out.df$order <- ord.[order(ord.,decreasing=T)]

out.ls <- lapply(m.list.cntr1, function(x){
  get_plot_data(x,coef_no=c(1,2))
})
out.df1 <- do.call(rbind,out.ls)
out.df1$dv <- c(rep(paste0("Exogamy L",c(1:10)),each=2),rep(paste0("Exogamy L","11-14"),each=2),rep(paste0("Exogamy L",c(15:16)),each=2))
ord. <- c(ticks+0.2,ticks-0.4)
out.df1$order <- ord.[order(ord.,decreasing=T)]
out.df1$what <- factor(rep(c("Cash Crops (Baseline)","Publications (Baseline)"),13))


# combine
out.df.both <- rbind(out.df1,out.df)
out.df.both <- out.df.both[order(out.df.both$order,decreasing = T),]

col1 <- wes_palette("Darjeeling1",5,"discrete")[2]
col2 <- wes_palette("Darjeeling1",5,"discrete")[3]
col3 <- wes_palette("Darjeeling1",5,"discrete")[5]
col4 <- wes_palette("Darjeeling1",15,"continuous")[2]


out.df.both$what <- factor(out.df.both$what,levels=c("Cash Crops (Diversity Control)","Cash Crops (Baseline)","Publications (Diversity Control)","Publications (Baseline)"))



# do the plot from both models
p <- ggplot(out.df.both)
p <- p + geom_point(size=2.25,aes(x=beta,y=order,color=what,shape=what,fill=what)) +
  geom_errorbarh(aes(x=beta,y=order, xmin=lb, xmax=ub,color=what), size=1, height=0.0) +
  geom_vline(xintercept=0,linetype="dotted", size=0.6) +
  scale_y_continuous(breaks=ticks,minor_breaks = NULL,
                     labels=c(paste0("Exogamy L",c(1:10)),"Exogamy L11-14",paste0("Exogamy L",c(15:16)))) +
  #scale_x_continuous(minor_breaks = seq(0 , 0.55, 0.05), breaks = seq(0, 0.55, 0.1)) +
  labs(x = "Coefficients and 95% Confidence Intervals", y = "Exogamy at Ethnologue Levels",
       title="Cash Crops, Publications & Inter-Ethnic Marriages",
       subtitle="Treatment defined geographically"
       #,caption="Cash crop value per sqkm in 1960 USD (Poly.)\nCash Crops (SAR)\nCash Crop Suitability (Poly)\nCash Crops (Instrumented with Suitability)"
  ) +
  theme_minimal(base_size=14) +
  theme(axis.text.y = element_text(size=10),legend.position = "bottom") +
  scale_color_manual(values=c("Cash Crops (Diversity Control)" = col1, "Cash Crops (Baseline)" = col3, "Publications (Diversity Control)" =col2, "Publications (Baseline)" =col4),name="Treatment/Model") +
  scale_fill_manual(values=c("Cash Crops (Diversity Control)" = col1, "Cash Crops (Baseline)" = col3, "Publications (Diversity Control)" =col2, "Publications (Baseline)" =col4),name="Treatment/Model") +
  scale_shape_manual(values=c("Cash Crops (Diversity Control)" = 24, "Cash Crops (Baseline)" = 22, "Publications (Diversity Control)" = 25, "Publications (Baseline)" =23),name="Treatment/Model")
p <- p + guides(color=guide_legend(ncol=2,nrow=2,byrow=TRUE),
                fill=guide_legend(ncol=2,nrow=2,byrow=TRUE),
                shape=guide_legend(ncol=2,nrow=2,byrow=TRUE))
p
p + ggsave(paste0(fig.path,"dhs_figA36.pdf"),width=8,height=9)
